Escorregamentos de taludes no Sudeste do Brasil são causados principalmente, pelo efeito da água proveniente das chuvas. Nos últimos anos, vem se incrementando o número de desastres naturais, ao passo são registradas mudanças climáticas, que podem exercer influência na ocorrência de chuvas extremas. Muitas encostas permanecem grande parte do ano com o solo em estado não saturado, porém variações nas condições ambientais podem ocasionar mudanças bruscas da sucção, reduzindo ou até mesmo eliminando-a e gerando pressões neutras positivas. A dissertação apresenta, um estudo sobre a influência das chuvas, consideradas extremas, no processo de infiltração e de este nos eventos de escorregamentos, considerados catastróficos pela sua dimensão, e que causaram prejuízos ambientais, econômicos e sociais no Brasil. Para o estudo foram selecionados dois eventos de escorregamentos translacionais rasos relativamente típicos, considerados catastróficos, um deles aconteceu na região da Serra de Cubatão em janeiro do ano 1985, e o outro na Região Serrana do Rio de Janeiro em janeiro de 2011. Estes dois eventos apresentaram características de precipitações e mecanismos de escorregamentos próprios, que permitem ilustrar os diferentes mecanismos atuantes em cada caso. / Landslide in southeastern Brazil, are mainly caused by the effect of water from rainfall in infiltration process, in recent years has been increasing the number of natural disasters, while climate change that may exercising influence on the occurrence of extreme rainfall are recorded . Many slopes remain a large part of the year with unsaturated soil condition; however, changes in environmental conditions can cause sudden changes of suction, reducing or even deleting it and generate positive pore pressures. This dissertation presents a study about the influence of rainfall, considered extreme in the infiltration process and this one in the events regarded by their size of catastrophic landslides, which caused environmental, economic and social losses in Brazil. For the study were selected two events of shallow translational landslides relatively typical, considered catastrophic, one of them occurred in the Serra de Cubatão region on January 1985 and the other in the mountainous region of Rio de Janeiro on January 2011. Both events exhibit characteristics of rainfall and sliding mechanisms themselves, allowing illustrate the different mechanisms active in each case.

Escorregamentos de taludes no Sudeste do Brasil são causados principalmente, pelo efeito da água proveniente das chuvas. Nos últimos anos, vem se incrementando o número de desastres naturais, ao passo são registradas mudanças climáticas, que podem exercer influência na ocorrência de chuvas extremas. Muitas encostas permanecem grande parte do ano com o solo em estado não saturado, porém variações nas condições ambientais podem ocasionar mudanças bruscas da sucção, reduzindo ou até mesmo eliminando-a e gerando pressões neutras positivas. A dissertação apresenta, um estudo sobre a influência das chuvas, consideradas extremas, no processo de infiltração e de este nos eventos de escorregamentos, considerados catastróficos pela sua dimensão, e que causaram prejuízos ambientais, econômicos e sociais no Brasil. Para o estudo foram selecionados dois eventos de escorregamentos translacionais rasos relativamente típicos, considerados catastróficos, um deles aconteceu na região da Serra de Cubatão em janeiro do ano 1985, e o outro na Região Serrana do Rio de Janeiro em janeiro de 2011. Estes dois eventos apresentaram características de precipitações e mecanismos de escorregamentos próprios, que permitem ilustrar os diferentes mecanismos atuantes em cada caso. / Landslide in southeastern Brazil, are mainly caused by the effect of water from rainfall in infiltration process, in recent years has been increasing the number of natural disasters, while climate change that may exercising influence on the occurrence of extreme rainfall are recorded . Many slopes remain a large part of the year with unsaturated soil condition; however, changes in environmental conditions can cause sudden changes of suction, reducing or even deleting it and generate positive pore pressures. This dissertation presents a study about the influence of rainfall, considered extreme in the infiltration process and this one in the events regarded by their size of catastrophic landslides, which caused environmental, economic and social losses in Brazil. For the study were selected two events of shallow translational landslides relatively typical, considered catastrophic, one of them occurred in the Serra de Cubatão region on January 1985 and the other in the mountainous region of Rio de Janeiro on January 2011. Both events exhibit characteristics of rainfall and sliding mechanisms themselves, allowing illustrate the different mechanisms active in each case.

Depressions in the prairie pothole region (PPR) are commonly referred to as sloughs and were formed during the most recent glacial retreat, ~10-17 kyrs ago. They are hydrologically isolated, as they are not permanently connected by surface inflow or outflow channels. Extreme thunderstorms are common across the prairies and the hydrologic response of isolated wetlands to intense rainfall events is poorly understood. The purpose of this study was to compare the response of different landscape/ecological elements of a prairie wetland to snowmelt and extreme rainstorms. Comparisons were completed by investigating the spring snowmelts of 2005 and 2006 and the rainstorm event of June 17 - 18, 2005, in which 103 mm fell at the St. Denis National Wildlife Area (NWA) Saskatchewan, Canada (106°06'W, 52°02'N). The wetland was separated into five landscape positions, the pond center (PC), grassed edge (GE), tree ring (TR), convex upland (CXU), and concave upland (CVU). Comparison of the rainfall of June 17 18, 2005 with the spring snowmelts of 2005 and 2006 indicates that the hydrologic consequences of these different events are similar. Overland flow, substantial ponding in lowlands, and recharge of the groundwater occur in both cases. Analysis of this intense rainfall has provided evidence that common, intense rainstorms are hydrologically equivalent to the annual spring snowmelt, the major source of water for closed catchments in the PPR.

Depressions in the prairie pothole region (PPR) are commonly referred to as sloughs and were formed during the most recent glacial retreat, ~10-17 kyrs ago. They are hydrologically isolated, as they are not permanently connected by surface inflow or outflow channels. Extreme thunderstorms are common across the prairies and the hydrologic response of isolated wetlands to intense rainfall events is poorly understood. The purpose of this study was to compare the response of different landscape/ecological elements of a prairie wetland to snowmelt and extreme rainstorms. Comparisons were completed by investigating the spring snowmelts of 2005 and 2006 and the rainstorm event of June 17 - 18, 2005, in which 103 mm fell at the St. Denis National Wildlife Area (NWA) Saskatchewan, Canada (106°06'W, 52°02'N). The wetland was separated into five landscape positions, the pond center (PC), grassed edge (GE), tree ring (TR), convex upland (CXU), and concave upland (CVU). Comparison of the rainfall of June 17 18, 2005 with the spring snowmelts of 2005 and 2006 indicates that the hydrologic consequences of these different events are similar. Overland flow, substantial ponding in lowlands, and recharge of the groundwater occur in both cases. Analysis of this intense rainfall has provided evidence that common, intense rainstorms are hydrologically equivalent to the annual spring snowmelt, the major source of water for closed catchments in the PPR.

Future changes in climate and land use are likely to affect catchment hydrological responses and consequently influence the amount of runoff reaching roads. Blockages and damage to under-dimensioned infrastructure can be extremely costly for the regions affected. This study aims to produce scientifically well-founded suggestions on adaptation of road drainage systems to climate changes resulting in more frequent floods. This thesis demonstrates the need to integrate aspects of climate change and land use impacts into the planning and practice of road construction and maintenance in Sweden. Tools such as hydrological models are needed to assess impacts on discharge dynamics. Identifying a ‘best’ practically performing hydrological model is often difficult due to the potential influence of modeller subjectivity on calibration procedure, parameter selection, etc. Hydrological models may need to be selected on a case-by-case basis and have their performance evaluated on an application-by-application basis. The work presented here began by examining current practice for road drainage systems in Sweden. Various hydrological models were then used to calculate the runoff from a catchment adjacent to a road and estimate changes in peak discharge and total runoff resulting from simulated land use measures. Overall, the results indicate that the specific effect of land use measures on catchment discharge depend on their spatial distribution and on the size and timing of storm events. Scenarios comprising a changing climate up to 2050 or to 2100 and forest clear-cutting were used to determine whether the current design of road drainage construction is sufficient for future conditions. Based on the findings, the approach developed can be used for similar studies, e.g. by the Swedish Transport Administration in dimensioning future road drainage structures to provide safe and robust infrastructure. Furthermore, a statistical method was developed for estimating and mapping flood hazard probability along roads using road and catchment characteristics. The method allows flood hazards to be estimated and provides insight into the relative roles of landscape characteristics in determining road-related flood hazards. Overall, this method provides an efficient way to estimate flooding hazards and to inform the planning of future roadways and the maintenance of existing roadways. / <p>QC 20140130</p>

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第18562号 / 工博第3923号 / 新制||工||1603(附属図書館) / 31462 / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 寶 馨, 教授 中北 英一, 教授 田中 茂信 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

This cumulative dissertation includes four peer-reviewed and published articles. It evaluates three open-access radar quantitative precipitation estimate (QPE) products from the German Weather Service (DWD) with different temporal resolutions. The improved length and quality of the DWD’s radar QPE products allows a detailed assessment of existing statistical precipitation characteristics and scaling laws, which are established on the basis of traditional point measurements only. The focus of the thesis is on heavy to extreme rainfall and scaling characteristics in time and space. The first publication is a comprehensive assessment of spatio-temporal heavy rainfall pattern in context of urban rainfall modification. The analysis identifies storm alteration by the city of Berlin using the RADOLAN-RW product, suitable for event analysis. Six storm categories were identified and newly introduced tools, such as the amplification factor helped to quantify the changes. The second and third publications focus on the re-evaluation of point-based findings from literature. The first compares depth-duration relationships based on 400,000+ grid cells within Germany for durations of 10 min to 3 days based on 16 years of RADKLIM-YW (5 min and 1 km spatio-temporal resolution) with a well-established global rainfall maxima curve. The German regional curve showed a 'three-phase-regime', governed by the temporal structure of very few extreme rainfall events. Three groups of curve characteristics for single grid cells were identified, based on the rainstorms that had occurred at the individual location. The third article shows the significance of using moving time interval maxima (M-Maxima) over fixed maxima (F-Maxima) and also helps to describe the probabilistic nature of the distribution of potential correction factors, in this case the Sampling Adjustment Factor (SAF), more accurately. It uses both RADKLIM products in order to compare different base resolutions and its effects on the results. Findings add new insights into the importance of identifying good correction factors and also consider the distribution of them instead of using average factors as usually done in practice. The fourth publication studies a new method to extrapolate extreme rainfall to sub-pixel scale via a simple scaling approach, based on 19 years of RADKLIM-RW (hourly and 1 km spatio-temporal resolution) and four regions within Germany of each 256 km x 256 km. Almost smooth power laws were observed when looking at the depth-area-relationships, depending on the considered data length and regions. Closer to the resolution of the radar data (1x1 km²), other influencing factors lead to a shift in rainfall characteristics and thus a bend of the relationship. The two rainfall classes of more convective and more advective characteristics generally had a strong influence on all results of the thesis and are highly dependent on the temporal resolution of the data. The gridded radar QPE data helped to reveal characteristics such as the correlation of small areas with high rain rates (connected to convective pattern) and larger areas with lower rain rates (connected to advective pattern). The analysed radar QPE products are suitable for analysing spatial and temporal rainfall pattern. However, for extreme values, uncertainty remains, since it is not clear if very extreme values are outliers or 'true' observations. / Diese kumulative Dissertation umfasst vier begutachtete und veröffentlichte Artikel. Sie wertet drei frei zugängliche Radarkomposite (QPE) des Deutschen Wetterdienstes (DWD) mit unterschiedlichen zeitlichen Auflösungen aus. Die verbesserte Länge und Qualität dieser Produkte ermöglicht eine detaillierte Bewertung vorhandener Niederschlagscharakteristika, die auf Punktmessungen beruhen. Der Schwerpunkt der Arbeit liegt dabei auf Stark- bis Extremniederschlägen und deren Skalierungseigenschaften. Die erste Veröffentlichung ist eine umfassende Bewertung der raum-zeitlichen Starkregenmuster im Kontext der städtischen Niederschlagsmodifikation. Die Analyse identifiziert den Einfluss der Stadt Berlins auf Starkregenereignisse unter Verwendung des RADOLAN-RW-Produkts. Sechs Kategorien von Niederschlagsmodifikationen wurden identifiziert und neu eingeführte Werkzeuge, wie der Verstärkungsfaktor, halfen bei der Quantifizierung der Veränderungen. Die zweite und dritte Publikationen konzentrieren sich auf die Neubewertung von punktbasierten Erkenntnissen aus der Literatur. Erstere vergleicht Niederschlags-Dauer-Beziehungen auf der Basis von mehr als 400.000 Rasterzellen innerhalb Deutschlands für Dauern von 10 min bis 3 Tagen auf der Grundlage von 16 Jahren RADKLIM-YW (5 min und 1 km räumlich-zeitliche Auflösung) mit einer bekannten globalen Niederschlagsmaximumkurve. Die regionale Kurve in Deutschland zeigte ein 'Drei-Phasen-Regime', das durch die zeitliche Struktur von sehr wenigen extremen Niederschlagsereignissen bestimmt wird. Es wurden drei Gruppen von Kurvencharakteristika für einzelne Gitterzellen identifiziert, die auf den am jeweiligen Standort aufgetretenen Regenfällen basieren. Zweitere zeigt die Bedeutung der Verwendung von gleitenden (M-Maxima) gegenüber festen Niederschlagsmaxima (F-Maxima) und hilft dabei, die probabilistische Natur der Verteilung potenzieller Korrekturfaktoren, in unserem Fall des 'Sampling Adjustment Factor' (SAF), genauer zu beschreiben. Es wurden beide RADKLIM-Produkte verwendet, um verschiedene Basisauflösungen und ihre Auswirkungen auf die Ergebnisse zu vergleichen. Die Ergebnisse liefern neue Erkenntnisse darüber, wie wichtig es ist, gute Korrekturfaktoren zu ermitteln und auch deren Verteilung zu berücksichtigen, anstatt wie in der Praxis üblich Durchschnittsfaktoren zu verwenden. Die vierte Veröffentlichung untersucht eine neue Methode zur Extrapolation extremer Niederschläge mittels eines einfachen Skalierungsansatzes, basierend auf 19 Jahren RADKLIM-RW (stündliche und 1 km räumlich-zeitliche Auflösung) und vier Regionen in Deutschland mit jeweils 256 km x 256 km. Es wurden nahezu perfekte Potenzgesetze in der Beziehung von Niederschlag und Fläche beobachtet, abhängig von der betrachteten Datenlänge und den Regionen. Nahe an der Auflösung des Radars (1x1 km²) knicken die Beziehungen ab, was auf eine Veränderung der Niederschlagscharakteristika hinweist. Die beiden Niederschlagsklassen mit eher konvektiven und eher advektiven Eigenschaften hatten generell einen starken Einfluss auf alle Ergebnisse der Arbeit und sind stark von der zeitlichen Auflösung der Daten abhängig. Die Radarkomposite halfen dabei, Merkmale wie die Korrelation von kleinen Gebieten mit hohen Niederschlagsmengen (verbunden mit konvektiven Mustern) und größeren Gebieten mit niedrigeren Niederschlagsmengen (verbunden mit advektiven Mustern) aufzuzeigen. Die analysierten Radarkomposite sind für die Analyse räumlicher und zeitlicher Niederschlagsmuster geeignet. Bei Extremwerten bleibt jedoch eine gewisse Unsicherheit, da nicht klar ist, ob es sich bei sehr extremen Werten um Ausreißer oder 'echte' Beobachtungen handelt.

Extreme rainfall statistics are important for the design and management of the water resource infrastructure. The standard approach for extreme rainfall event severity assessment is the Intensity-Duration-Frequency (IDF) method. However, this approach does not consider the spatial context of rainfall and consequently does not properly describe rainfall storm severity, nor rarity. This study provides a critical account of the current standard practice and presents an approach that takes into consideration both the spatial context of rainfall storms, and indirectly incorporates runoff to produce a representative approach to assessing urban rainfall storm severity in terms of flood potential. A stepwise regression analysis was performed on a dataset of individual rainfall storm characteristics to best represent documented basement floodings in the City of Edmonton. Finally, the urban rainfall storm flood severity index was shown to be most representative of the documented basement floodings' severity when compared to that of the IDF method.

Extreme rainfall statistics are important for the design and management of the water resource infrastructure. The standard approach for extreme rainfall event severity assessment is the Intensity-Duration-Frequency (IDF) method. However, this approach does not consider the spatial context of rainfall and consequently does not properly describe rainfall storm severity, nor rarity. This study provides a critical account of the current standard practice and presents an approach that takes into consideration both the spatial context of rainfall storms, and indirectly incorporates runoff to produce a representative approach to assessing urban rainfall storm severity in terms of flood potential. A stepwise regression analysis was performed on a dataset of individual rainfall storm characteristics to best represent documented basement floodings in the City of Edmonton. Finally, the urban rainfall storm flood severity index was shown to be most representative of the documented basement floodings' severity when compared to that of the IDF method.

Regionalization of hydrometeorological variables such as rainfall and temperature is necessary for various applications related to water resources planning and management. Sampling variability and randomness associated with the variables, as well as non-availability and paucity of data pose a challenge in modelling the variables. This challenge can be addressed by using stochastic models that utilize information from hydrometeorologically similar locations for modelling the variables. A set of locations that are hydrometeorologically similar are referred to as homogeneous region or pooling group and the process of identifying a homogeneous region is referred to as regionalization. The thesis concerns development of new approaches to regionalization of (i) extreme rainfall,(ii) maximum and minimum temperatures, and (iii) rainfall together with maximum and minimum temperatures. Regionalization of extreme rainfall and frequency analysis based on resulting regions yields quantile estimates that find use in design of water control (e.g., barrages, dams, levees) and conveyance structures (e.g., culverts, storm sewers, spillways) to mitigate damages that are likely due to floods triggered by extreme rainfall, and land-use planning and management. Regionalization based on both rainfall and temperature yield regions that could be used to address a wide spectrum of problems such as meteorological drought analysis, agricultural planning to cope with water shortages during droughts, downscaling of precipitation and temperature. Conventional approaches to regionalization of extreme rainfall are based extensively on statistics derived from extreme rainfall. Therefore delineated regions are susceptible to sampling variability and randomness associated with extreme rainfall records, which is undesirable. To address this, the idea of forming regions by considering attributes for regionalization as seasonality measure and site location indicators (which could be determined even for ungauged locations) is explored. For regionalization, Global Fuzzy c-means (GFCM) cluster analysis based methodology is developed in L-moment framework. The methodology is used to arrive at a set of 25 homogeneous extreme rainfall regions over India considering gridded rainfall records at daily scale, as there is dearth of regionalization studies on extreme rainfall in India Results are compared with those based on commonly used region of influence (ROI) approach that forms site-specific regions for quantile estimation, but lacks ability to delineate a geographical area into a reasonable number of homogeneous regions. Gridded data constitute spatially averaged rainfall that might originate from a different process (more synoptic) than point rainfall (more convective). Therefore to investigate utility of the developed GFCM methodology in arriving at meaningful regions when applied to point rainfall data, the methodology is applied to daily rainfall records available for 1032 gauges in Karnataka state of India. The application yielded 22 homogeneous extreme rainfall regions. Experiments carried out to examine utility of GFCM and ROI based regions in arriving at quantile estimates for ungauged sites in the study area reveal that performance of GFCM methodology is fairly close to that of ROI approach. Errors were marginally lower in the case of GFCM approach in analysis with observed point rainfall data over Karnataka, while its converse was noted in the case of analysis with gridded rainfall data over India. Neither of the approaches (CA, ROI) was found to be consistent in yielding least error in quantile estimates over all the sites. The existing approaches to regionalization of temperature are based on temperature time series or their related statistics, rather than attributes effecting temperature in the study area. Therefore independent validation of the delineated regions for homogeneity in temperature is not possible. Another drawback of the existing approaches is that they require adequate number of sites with contemporaneous temperature records for regionalization, because the delineated regions are susceptible to sampling variability and randomness associated with the temperature records that are often (i) short in length, (ii) limited over contemporaneous time period and (iii) spatially sparse. To address these issues, a two-stage clustering approach is developed to arrive at regions that are homogeneous in terms of both monthly maximum and minimum temperatures ( and ). First-stage of the approach involves (i) identifying a common set of possible predictors (LSAVs) influencing and over the entire study area, and (ii) using correlations of those predictors with and along with location indicators (latitude, longitude and altitude) as the basis to delineate sites in the study area into hard clusters through global k-means clustering algorithm. The second stage involves (i) identifying appropriate LSAVs corresponding to each of the first-stage clusters, which could be considered as potential predictors, and (ii) using the potential predictors along with location indicators (latitude, longitude and altitude) as the basis to partition each of the first-stage clusters into homogeneous temperature regions through global fuzzy c-means clustering algorithm. A set of 28 homogeneous temperature regions was delineated over India using the proposed approach. Those regions are shown to be effective when compared to an existing set of 6 temperature regions over India for which inter-site cross-correlations were found to be weak and negative for several months, which is undesirable. Effectiveness of the newly formed regions is demonstrated. Utility of the proposed maxTminT homogeneous temperature regions in arriving at PET estimates for ungauged locations within the study area was demonstrated. The estimates were found to be better when compared to those based on the existing regions. The existing approaches to regionalization of hydrometeorological variables are based on principal components (PCs)/ statistics/indices determined from time-series of those variables at monthly and seasonal scale. An issue with use of PCs for regionalization is that they have to be extracted from contemporaneous records of hydrometeorological variables. Therefore delineated regions may not be effective when the available records are limited over contemporaneous time period. A drawback associated with the use of statistics/indices is that they (i) may not be meaningful when data exhibit nonstationarity and (ii) do not encompass complete information in the original time series. Consequently the resulting regions may not be effective for the desired purpose. To address these issues, a new approach is proposed. It considers information extracted from wavelet transformations of the observed multivariate hydrometeorological time series as the basis for regionalization by global fuzzy c-means clustering procedure. The approach can account for dynamic variability in the time series and its nonstationarity (if any). Effectiveness of the proposed approach in forming homogeneous hydrometeorological regions is demonstrated by application to India, as there are no prior attempts to form such regions over the country. The investigations resulted in identification of 29 regions over India, which are found to be effective and meaningful. Drought Severity-Area-Frequency (SAF) curves are developed for each of the newly formed regions considering the drought index to be Standardized Precipitation Evapotranspiration Index (SPEI).